The invention relates to an arrangement and a method for identifying persons by recognizing detectable body features. The arrangement is intended to be usable portably.
Determining the identity of a person, or confirming the claimed identity, is one of the most important security tasks in an information technology context. The intention is to be able to distinguish authorized persons from unauthorized persons. The authenticity of persons, and therefore correspondence of a claimed identity with the real identity, must be verifiable. Besides the authentication of persons with the aid of knowledge, for example of a secret number, or possession, for example of a card, i.e. a temporary mechanism, a person is also intended to be assigned so-called attribute features such as physical properties or behavior patterns, which are directly and in general permanently associated with a person. These attribute features may be examined and determined by biometric methods and systems. So-called biometric recognition is carried out with the aid of measurable body features which are assigned to a particular individual. These features are inseparably associated with a person and do not first need to be assigned to them; they cannot be lost and the person does not need to be able to remember them (like a secret number) and they cannot in general be kept secret i.e. these features are apparent, for example face, fingers. Since these features are not transferable, the identity can be assigned uniquely to a person who has been determined correctly by a biometric method.
The demand for reliable person identifications is currently increasing significantly. The problem of person identification is occurring ever more frequently in the field of for example e-commerce, in access control systems, in counter-terrorism etc. Although identification by possession, for example of a pass, still serves its purpose, it is however becoming less important in the modern world with its frequent electronic communication. Biometry has for this reason been gaining importance, particularly in recent times, since it relates the person identification to an individual's features which are unique and to some extent unchangeable, or are stable over a long period of time.
Growing and more complex technologies increasingly require accurate and automated person identification. Access to particular objects can be regulated by particular rights with the aid of person identification. Anyone who has been identified successfully, and therefore accepted, receives the predetermined privileges. When such a method is simpler but also a more reliable, the quality of the person recognition is commensurately better and the acceptance of the biometric method is therefore greater.
A large number of biometric methods are known, the following currently being the methods discussed most                fingerprint recognition        face recognition        iris recognition.        
Fingerprint Method:
This method has been available for about 100 years for identifying persons. It is used predominantly in the field of criminal prosecution. In the IT-based (information technology) automated form, the digital fingerprint method is a biometric method with high recognition power. For recording the fingerprint in automatic fingerprint recognition, special sensors of optical, capacitive, semiconductor-based, thermal or direct optical technology are used. For example, attempts are being made to measure skin impedances with ultrasound sensors.
Regardless of the nature of the fingerprint recording, the method is always provided with a grayscale image of the finger, i.e. the fingerprint. This image is processed further so that correct matching results (correspondence) can be achieved with the enhanced image. The image processing steps involve for instance reducing the image noise, enhancing the image and detecting the features. The extraction of characteristic traits from the image may be carried out with the aid of various methods. It is possible to record either the entire image, as in global pattern matching, relevant parts thereof or the minutiae of type, position and direction. Comparison of these measured characteristic traits with stored setpoint values shows whether the prints come from the same finger and therefore from one person in particular.
Face Recognition:
In biometric face recognition, a person's face is recorded using a camera and compared with one or more previously stored face images. The image is initially digitized, for example in a PC. The recognition software then locates the face and calculates its characteristic properties. The result of this calculation, the so-called template, is compared with the templates (patterns, models) of the stored face images. The exception to this is when the original image is used as a reference image, which is compared against a current original image for the recognition process.
There are different types of approaches for face recognition, with particular key elements being used. In most face recognition methods, the characteristic features of the facial appearance are determined with the aid of a digitized image. Above all, those features of the face are used which do not change constantly owing to the facial expression, i.e. upper edges of the eye sockets, the regions around the cheekbones and the side parts of the mouth. In principle, comparison of the characteristic facial features with the corresponding reference features is carried out by classical image processing and image analysis methods, for instance, after locating the eyes, calculating the facial features with the aid of a grid network which is placed over the face. One subgroup of biometric face recognition is the so-called eigenface method, which is used above all in the field of person identification. Lastly, there are initial approaches to 3D face recognition.
Iris Recognition:
Between the iris (pigmented tissue) and the cornea of the human eye, there are complex connective tissue structures resembling bands and combs. These structures are different in each individual. They even differ in identical twins. Furthermore, they vary little during a lifetime in a healthy eye. The image of the iris, recorded externally by a conventional camera (for example a CCD camera) allows the structures to be recognized and is therefore suitable as a unique recognition feature.
In individuals with dark eye coloration, however, the structures can be recognized only with difficulty in visible light. Biometric iris recognition systems therefore illuminate the iris from a distance of about one meter with light in the near infrared range, which is virtually invisible to the eye. This penetrates through the “pigment” of the human eye (melanin) better than visible light. A recording of the iris structures can therefore be made for all humans with healthy eyes, without dazzling. From the recorded images, by mathematical methods developed specially for this purpose, a unique data set is formed which serves as a so-called “template” for the biometric recognition.
The other biometric methods include signature recognition, speech or voice recognition, hand geometry or recognition of the typing behavior on a keyboard.